Learn R Programming

ldamatch (version 1.0.3)

Selection of Statistically Similar Research Groups

Description

Select statistically similar research groups by backward selection using various robust algorithms, including a heuristic based on linear discriminant analysis, multiple heuristics based on the test statistic, and parallelized exhaustive search.

Copy Link

Version

Install

install.packages('ldamatch')

Monthly Downloads

263

Version

1.0.3

License

MIT + file LICENSE

Maintainer

Last Published

April 14th, 2024

Functions in ldamatch (1.0.3)

.get_if_args_are_missing

Determines which arguments for a function, which is its caller by default.

.decrease_group_sizes

Creates all group sizes by reducing one group in all rows of grpsizes.

.sort_group_sizes

Orders rows by similarity to expected group size proportions.

Gets value for ldamatch global parameter.

A univariate halting test using the Kolmogorov-Smirnov Test, which must be satisfied for all condition pairs.

A univariate halting test using Fisher's exact test.

estimate_exhaustive

Estimates the maximum number of cases to be checked during exhaustive search.

Criterion function for f_halt.

.warn_about_extra_params

Warns about extra (i.e. unused) parameters.

Criterion function for l_halt.

Criterion function for t_halt.

Criterion function for ks_halt.

search_heuristic3

Finds matching using depth-first search, looking ahead n steps.

.check_subspaces_for_group_size_setup

Searches over all possible subspaces for specified group size setup.

.normalize_props

Normalizes the props parameter for match_groups().

search_heuristic4

Finds matching using depth-first search, looking ahead n steps.

.vector_list_to_string

Creates string from list of vectors.

.choose_subject_with_best_p_value_from_subject_tuples

Chooses best one(s) of a set of subjects having the best p-value(s).

.internally_compare_ldamatch_outputs

Compares outputs of ldamatch runs using internally normalized parameters.

.calc_subject_balance_divergence

Characterizes closeness of actual group sizes to what is expected.

Uniquifies a list.

An infinitesimally small amount, used to check if values are approximately the same.

.normalize_max_removed_per_cond

Normalizes max_removed_per_cond parameter for match_groups() and estimate_exhaustive().

A univariate halting test using the t-test, which must be satisfied for all condition pairs.

Creates a matched group via backward selection.

.search_heuristic_with_lookahead

Finds matching using depth-first search, looking ahead n steps.

A univariate halting test using Levene's test.

Wrapper to foreach::foreach called from .choose_best_subjects.

Recycles threshold values for halting tests.

Flips logical vector at specified indices

A multivariate halting test appropriate for more than two condition levels.

matching_methods

The available methods for matching.

search_heuristic2

OBSOLETE: Finds matching using depth-first search recursively.

search_exhaustive

Searches the space backwards, prefering more subjects and certain group size proportions.

ldamatch-package

ldamatch: Selection of Statistically Similar Research Groups.

parallelized_matching_methods

The available parallelized methods for matching.

nondeterministic_matching_methods

The available nondeterministic methods for matching.

Searches by randomly selecting subspaces with decreasing expected size.

Sets value for ldamatch global parameter.

Criterion function for U_halt.

A univariate halting test using the Wilcoxon test, which must be satisfied for all condition pairs.

A univariate halting test using the Anderson-Darling test.

Calculates basic metrics about ldamatch search result.

.choose_most_frequently_chosen_subject_from_subject_tuples

Chooses best one(s) of a set of subjects having the best p-value(s).

Criterion function for ad_halt.

Combines current best and candidate sets, keeping the highest metric value.

Returns smallest halting_test-threshold ratio, or 0 if less than 1.

compare_ldamatch_outputs

Compares outputs of ldamatch runs.

Calculates p-value using specified halting test.

.create_Cartesian_iterable

Creates Cartesian product of iterators.

create_halting_test

Creates halting test from multiple tests.

.choose_best_subjects

Chooses best set of subjects in a set.

.choose_best_test_statistic

Chooses rows with best test statistic.

.calc_multipliers

Calculates multipliers used in search_random.

.calc_p_thresh_ratio

Calculates p-value-threshold ratio.

.get_halting_test

Returns halting tests for names, or checks if pass functions are suitable.

.apply_crit_to_condition_pairs

Returns smallest value from .apply_crit for all condition pairs.

.get_human_readable

Returns human readable format for number of seconds.